Technical Trading

Does technical analysis work after accounting for luck and trading frictions? More specifically, can traders reliably identify technical rules that generate future net outperformance? In the January 2008 version of their paper entitled “Technical Trading Revisited: Persistence Tests, Transaction Costs, and False Discoveries”, Pierre Bajgrowicz and Olivier Scaillet investigate the economic value of technical trading rules applied to long-run daily Dow Jones Industrial Average (DJIA) data. Their approach includes: (1) a new measure of data snooping bias to distinguish between luck and true forecasting power in backtesting; (2) out-of-sample persistence testing of recently successful trading rules; (3) determination of whether certain trading rules work consistently under specific economic conditions; and, (4) incorporation of trading costs. Using daily DJIA price and volume data for January 1897 through July 2007 to test 7,846 rules (filters, moving averages, support and resistance, channel breakouts and on-balance volume averages), they conclude that: Keep Reading

A reader inquired about a test of the BMW Method, defined as follows:

“I trust the CAGR. That is the compound average growth rate. I look back 30 years to get a base number to work from and I then calculate the range of CAGR’s that encompass the full range of stock prices over that 30 year period. The curves are extended into the future by 5 to 10 years and I have a complete picture of what has been and what can be if the business just rolls on along. I buy stocks when they are priced significantly below the lowest historical 30 year CAGR. It happens often. If I cannot find a business that is significantly below the low CAGR, I will settle for some that are on their 30 year lows or just below that level. These do not enthuse me nearly as much, but they will rebound also. The history proves it. This is a definite buy low, sell high concept…except it works. In fact, I want anyone to explain in detail how it cannot work.”

This description is not a precise specification. To test the underlying concept, we hypothesize that the short-term compound growth rate of a broad market index tends to revert to a longer-term compound growth rate. If we enter the market after intervals of relatively low short-term growth and exit after intervals of relatively high short-term growth, we may be able to outperform a buy-and-hold strategy. We use the S&P 500 index to represent the stock market because of its long history. For trading precision we use daily closing levels of the index, with one-year intervals for the short-term growth trend and 30-year and five-year intervals for the long-term growth trend. Using S&P 500 index closing levels for 1/3/50 through 3/3/08, we find that… Keep Reading

Here is a simple test of the usefulness of the Relative Strength Index (RSI) and the Moving Average Convergence/Divergence (MACD), combined, in search of more concentrated abnormal returns. Using those signals and daily dividend-adjusted SPY closing prices from 1/29/93 (the earliest available) through 2/29/08, we find that: Keep Reading

Here is a simple test of the Moving Average Convergence/Divergence (MACD), as calculated using the Exponential Moving Average (EMA) template at StockCharts.com, on a tradable proxy for the S&P 500 index. MACD is the difference between the 26-day EMA price and the 12-day EMA price for an asset. A bullish (bearish) crossover occurs when MACD moves above (below) its 9-day EMA. To reduce the number of very short-term MACD trades, we filter out “close calls” by requiring MACD to reach a level 25% above or below its 9-day EMA before triggering a trade. Using daily dividend-adjusted closing prices for the S&P Depository Receipts Trust (SPY) from 1/29/93 (the earliest available) through 2/29/08, we find that: Keep Reading

A reader asked: “Jason Kelly from the Kelly Newsletter posted this remark in January 2008: ‘A good way to judge trading opportunities on indexes is by watching their MACD and RSI scores. Both together, along with the price chart, give good indications as to whether the odds favor rising or falling from here.’ Is this true?” Here is a simple test of the 14-day Relative Strength Index (RSI), as calculated by the template at StockCharts.com, on a tradable proxy for the S&P 500 index. Note that this indicator measures the strength of price for an asset relative to its own recent past, not relative to other assets. We use the conventional interpretation that values of RSI below 30 (above 70) indicate oversold (overbought) conditions ripe for reversion. Using daily dividend-adjusted closing prices for the S&P Depository Receipts Trust (SPY) from 1/29/93 (the earliest available) through 2/29/08, we find that: Keep Reading

A reader suggested that we evaluate the performance of Between the Hedges, a “portfolio manager’s commentary on investing and trading in the U.S. financial markets.” One prominent and systematic feature of the commentary in that blog is the daily net portfolio position, expressed as percentage long. This position changes frequently, and the portfolio manager presumably manages it to exploit expected short-term trends in the broad stock market. If the expectation has value, the net portfolio position should relate positively to near-term broad market behavior. Using the Between the Hedges daily net portfolio position for 2/2/04-2/26/08 (1,024 trading days) and contemporaneous daily data for the S&P 500 index, we find that: Keep Reading

Several readers have requested that we evaluate the market timing value of Tony Caldaro’s “Objective Elliott Wave (OEW)” analysis. Mr. Caldaro describes OEW as incorporating missing tenets, such that: “Applying these newfound tenets to the market, …the waves were crystal clear. The turning points were precise, to the day, because they were quantitatively derived. There was no question when a wave ended and another began.” Based on the record of “MEDIUM TERM” outlook synopses in Tony Caldaro’s daily commentary blog and contemporaneous daily data for the S&P 500 index over the period January 2006 through January 2008 (523 trading days), we conclude that: Keep Reading

A reader poses the following question: “Have you looked at IntelligentValue? They claim pretty impressive results, apparently certified by FinancialContent. Their Retracement-Value portfolio, particularly, shows impressive results [“508% in its 1st 18.5 months!”]. Are you able to evaluate this newsletter service?” Based on the information provided on IntelligentValue’s web site, especially the closed trade analysis for the [now removed] Retracement-Value portfolio (171 round-trip trades, apparently from portfolio inception on 5/16/06 through 1/9/08, with a starting portfolio value of $10,000), we conclude that: Keep Reading

Several readers have requested that we evaluate the expertise of Mark Leibovit, Chief Market Strategist for VRTrader.com, According to VRTrader.com: “His technical expertise is in volume analysis, providing short-term, high performance stock trades and market timing…” Based on the information provided at VRTrader.com, especially the “Track Record” encompassing 3,388 round-trip trades during 2001-2007, we conclude that: Keep Reading

A reader asked: “Please evaluate the performances of the The Trend Trade Letter and The Cheap Stocks Letter offered by Befriend the Trend Trading.” We focus here on the The Trend Trade Letter, which has a much larger sample of historical trades than its sibling. Both the company and newsletter names imply a momentum-centric trading approach. The newsletter focuses on fairly continuous short-term technical trading (long and short) of liquid, volatile stocks with no more than ten positions at a time. Based on the information provided on the Befriend the Trend Trading web site, especially the monthly closed trade lists for The Trend Trade Letter (over 1,300 round-trip trades, from inception on 10/7/02 through 12/11/07), we conclude that: Keep Reading